The seismic shothole drillers' log database and GIS for Northwest Territories and northern Yukon: an archive of near-surface lithostratigraphic surficial and bedrock geology data
Bibliographic record
Abstract
The seismic shothole drillers' log database provides baseline, near-surface (3-90 m; average 18.6 m) lithostratigraphic geoscience information on surficial, bedrock, hydro-, and permafrost geology. The revised and updated version 3 database contains 343,989 individual augered, or air-rotary drilled seismic shothole drillers' log records collected from 1952 to present. Originally published in 2007 as Open File 5465 (75,783 records) then updated in 2010 as Open File 6049 (275,871 records), the present database represents the sum total of all available archival holdings from Industry. Compiled in a Microsoft Access database, and graphically rendered in a GIS, the shothole data span the length and breadth of the Mackenzie corridor, Mackenzie Delta, and adjoining petroleum exploration regions of continental Northwest Territories and northern Yukon. The data, and numerous derivative thematic GIS and models stemming from this publication, provide an unparalleled and unique source of information that will benefit a wide variety of users (e.g., aboriginal organizations, communities, government, industry, land and water boards, regulators, and scientists), and applications (e.g., environmental assessments, infrastructure development, land use planning, resource management, and seismic exploration).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".